The comparison of W/Cu and W/ZrC composites fabricated through hot-press

In this study the W/Cu and W/ZrC composites have been fabricated by hot-press and then their mechanical properties were compared in addition to their ablation resistance. To produce W-20vol.%Cu composite at first stage the elemental W and Cu powders were ball milled for 3 h in rotation speed of 200 rpm, in which 2% nickel was added in order to reduce the density. The mixed powders were hot-pressed for 1 h at 1400 °C and compact pressure of 30 MPa. Additionally W/40vol.%ZrC composite has been fabricated by hot-pressing of mixed W and ZrC powders in 30 MPa and 2200 °C for 1 h. Since these materials are used at elevated temperature applications, where ablation is the main source of material failure, after producing the composites their ablation resistance was evaluated in a real condition. The results show that not only W–ZrC composite is better than W–Cu composite in mechanical properties, but also in ablation resistance.     

A Predictive Correlation for Dynamic Viscosity of Fatty Acid Methyl Esters and Biodiesel

The viscosity of biodiesel, which is a mixture of fatty acid methyl esters (FAME), is an important physical property in the injection and efficient combustion. In this study, a simple correlation, with only one adjustable parameter, is proposed for predicting the viscosity of FAME and their mixtures (biodiesel) as a function of temperature. First, the adjustable parameter of the correlation is calculated for various FAME. The average absolute relative deviation (AARD) is obtained to be 0.97% for 226 data points. Second, the adjustable parameter of FAME is connected to the number of carbon atoms and the number of double bonds to build a predictive correlation for the calculation of viscosity. The AARD for 226 data points is obtained to be 2.28%. Third, the proposed model is employed to predict the viscosity of biodiesel without introducing any new adjustable parameter. To predict the viscosity of biodiesel, the average of the adjustable parameter is applied to the correlation. The AARD of 2.96% is obtained for 185 data points comprised of 23 different biodiesels. To better understand the ability of the correlation in the estimation of the viscosity of biodiesel and FAME, a comparison is made between the present correlation and a number of correlations available in the literature.     

Intelligent power management strategy of hybrid distributed generation system

This paper describes a novel control strategy for active power flow in a hybrid fuel cell/battery distributed generation system. The method introduces an on-line power management by a hierarchical hybrid controller between dual energy sources that consist of a battery bank and a solid oxide fuel cell (SOFC). The proposed method includes an advance supervisory controller in the first layer which captures all of the possible operation modes. This layer has been developed by Stateflow toolbox and prepares a proper supervisory environment for this complex structure. In the second layer, an advanced fuzzy controller has been developed for power splitting between battery and fuel cell. With regards to the operation modes, the upper layer makes decision to choose the switching chain rules and corresponding controller in the second layer. Finally in the third layer, there are local controllers to regulate the set points of each subsystems to reach the best performance and acceptable operation indexes. Simulation results of a test system illustrate improvement in the operation efficiency of the hybrid system and the battery state of charge has been maintained at a reasonable level.     

Prediction of biodiesel properties and its characterization using fatty acid profiles

Biodiesel, the mono-alkyl esters of vegetable oils or animal fats, is an eco-friendly alternative to petrodiesel. The molecular structures of biodiesels, fatty acid methyl esters were applied to predict the characteristics of biodiesel fuels. Based on the structural similarity of biodiesel and petroleum fractions, molecular weight of biodiesel was correlated with other characteristics including boiling point, viscosity and specific-gravity in the form of three equations. For 24 different kinds of biodiesel, the minimum average relative deviation (ARD) of these correlations was calculated to be 0.68%. Moreover, two correlations were developed to predict viscosity and flash point of biodiesel as a function of weighted-average number of carbon atoms (N _C ) and weighted-average number of double bonds (N _DB ) with ARD 3.72% and 4.24% respectively. Also, a high degree of correlation was shown by the logarithmic function with ARD 0.30% between specific gravity and viscosity of biodiesel. Proposed predictive models were verified by experimental data.     

Surface deformation over the buried Nasr Abad salt diapir,Central Iran using interferometric synthetic aperture radar data

ABSTRACT

This study employs interferometric synthetic aperture radar (InSAR) data sets to monitor the surface deformation of the Nasr Abad buried salt diapir in the Central Basin of Iran. The Nasr Abad salt diapir is one of the largest buried salt diapirs in Iran and could be ideal site for oil/gas storage and industrial waste disposal. In this study, we use 40 advanced synthetic aperture radar (ASAR) images from Environmental Satellite (EnviSat) to analyse surface displacement rates of Nasr Abad diapir and its surrounding regions. A time series of line-of-sight (LOS) displacements on the residual cap above the buried diapir were obtained from both descending and ascending images between 2003 and 2010 by applying the Small-BAseline Subset (SBAS) technique. Tropospheric artefacts in the displacement interferograms were mitigated using the power-law correction method in Toolbox for Reducing Atmospheric InSAR Noise (TRAIN) software. Finally, the data for temperature, precipitation, and tidal forces were correlated with the time-series displacement results of four points that located on the residual cap. Our results indicate that surface above the diapir and an area of about 2 km² subsided with maximum LOS velocity of about 7 mm year^?1 for ascending images and 5 mm year^?1 for descending images. The amount of vertical subsidence derived from LOS decomposition in reactive stage of Nasr Abad salt body is about 7 mm year^?1. Comparing the temperature and precipitation data with the time series of displacement confirmed that the salt expands when temperatures increases and that salt flow accelerates when it is wet. The displacement pattern retrieved from InSAR analysis is in good agreement with intervals near maximum and minimum solid earth tides. Monitoring the activities of the Nasr Abad region over 7 years shows that the region of surface subsidence is confined to the area along the Khurabad and AbShirin-Shurab Fault zones in the southern Central Basin.     

Enumeration Order Equivalence in Rational Numbers

The enumeration of elements of c.e. sets in the theory of computability and computational complexity has already been investigated. However, the order of this enumeration has received less attention. The enumeration orders of elements of c.e. sets by means of Turing machines on natural numbers are investigated. In this paper, we consider the enumeration orders of elements of c.e. sets on rational numbers. We present enumeration order reducibility and enumeration order equivalence on rational numbers and propose some lemmas and theorems on these concepts. Also, we show that the theories here hold for Rc and we could repeat the same theories in this domain, in a same way.     

Application of artificial neural networks and genetic programming in vapor–liquid equilibrium of C1 to C7 alkane binary mixtures

In this study, the capacity of artificial neural networks (ANNs) and genetic programming (GP) in making possible, fast and reliable predictions of equilibrium compositions of alkane binary mixtures is investigated. A data set comprising 847 data points was gathered and used in both training the proposed ANN and generating the closed-form expressions of the GP procedure. The results obtained demonstrate the relative precision of the proposed ANN, while, on the other hand, exhibit that the GP model, although less precise, affords high CPU time efficiency and simplicity. Concisely, the proposed models can serve the purpose of being close first estimates for more thermodynamically rigorous vapor–liquid equilibrium calculation procedures and do obviate the necessity for the availability of a large set of experimental binary interaction coefficients. Mean absolute errors of 0.0100 and 0.0404 for liquid compositions and of 0.0054 and 0.0254 for vapor-phase mole fractions, for the proposed ANN and GP models, respectively, are a testament to the reliability of the proposed models.

     

Evaluation of peak and residual conditions of actively confined concrete using neuro-fuzzy and neural computing techniques

This paper investigates the ability of four artificial intelligence techniques, including artificial neural network (ANN), radial basis neural network (RBNN), adaptive neuro-fuzzy inference system (ANFIS) with grid partitioning, and ANFIS with fuzzy c-means clustering, to predict the peak and residual conditions of actively confined concrete. A large experimental test database that consists of 377 axial compression test results of actively confined concrete specimens was assembled from the published literature, and it was used to train, test, and validate the four models proposed in this paper using the mentioned artificial intelligence techniques. The results show that all of the neural network and ANFIS models fit well with the experimental results, and they outperform the conventional models. Among the artificial intelligence models investigated, RBNN model is found to be the most accurate to predict the peak and residual conditions of actively confined concrete. The predictions of each proposed model are subsequently used to study the interdependence of critical parameters and their influence on the behavior of actively confined concrete.

     

Green bio-synthesis of Ni/montmorillonite nanocomposite using extract of Allium jesdianum as the nano-catalyst for electrocatalytic oxidation of methanol

In this work, synthesis of Ni nanoparticles was carried out successfully by water extract of Allium jesdianum as a biochemical reducing agent in the presence of montmorillonite clay (MMT) as a natural solid support for the first time. Then the electrochemical activity of the synthesized nanocomposite was investigated in methanol electrocatalytic oxidation. MMT with high cation exchange capacity and nano layer structure was exposed to ion exchange conditions in nickel solution. Then Ni²⁺ ion exchanged form was used in this process as a source of ions and also capping agent. Water extract of Allium jesdianum used as a reducing agent due to abundant availability of phenolic and flavonoid contents. The synthesized Ni/MMT nanocomposite was characterized using UV-Vis spectroscopy (UV-Vis), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission electron microscopy (TEM) and Energy-dispersive X-ray spectroscopy (EDX). The surface of prepared modified electrode has been characterized using SEM to evaluate the morphology, showing uniform dispersion of Ni nanoparticles with mean diameter of 12 to 20 nm. The modified carbon paste electrode was then used in methanol electrocatalytic oxidation reaction. Methanol oxidation on the proposed modified electrode surface occurs at 0.6 V and 0.3 V in alkaline and acidic medium respectively. Also, the results showed the better performance of modified electrode toward methanol electrocatalytic oxidation in comparison with carbon paste electrode that is modified by ion exchanged MMT. Charge transfer coefficients and apparent charge transfer rate constant for the modified electrode in the absence of methanol in alkaline medium were respectively found as: α_a = 0.53, α_c = 0.37 and k_s = 1.6×10^-1 s^-1. Also, the average value of catalytic rate constant for the electrocatalytic oxidation of methanol by the prepared nano-catalyst was estimated to be about 0.9 L·mol^-1·s^-1 by chronoamperometry technique. The prepared electrode was also effective for electrocatalytic oxidation of ethanol and formaldehyde in alkaline medium.     

Mathematical modelling of CO2 facilitated transport through liquid membranes containing amines as carrier

An approximate analytical solution for the facilitated transport of carbon dioxide across a liquid membrane containing aqueous primary and secondary amine solutions has been developed in which the reversible reaction A(CO₂) + 2B(amine) AB(carbamate) + BH(protonated amine) occurs inside the liquid membranes. The current approximate analytical solution predicts the facilitated factor of CO₂ through the membrane and is based on the dimensionless, nonlinear diffusion‐reaction transport problem. The approximate analytical solution predicts the facilitation factors for the range from the moderate reaction rate to the equilibrium chemical reaction regime, allowing unequal diffusivities of complexes and carrier and cases of zero and nonzero permeate side solute concentrations. In the present mathematical model, a constant free carrier concentration is assumed throughout the membrane phase. In comparison with the numerically calculated results, the results obtained were found to be in well agreement.